Event Information:

• Thu

  12

  Dec

  2024

  SC Seminar: Gururaj Bhat

  11:45Room 32-349

  Gururaj Bhat, RPTU

  Title: Electricity market nodeling

  Abstract:

  Electricity is a unique and indispensable commodity that underpins nearly every aspect of
  modern life. Electricity prices are affected by numerous factors like fuel sources for power
  generation, infrastructure of the electricity grids, and weather, to name a few. Modelling
  electricity prices is a complex process due to its non-storable property and the different
  characteristics it exhibits, which are discussed in this work. Nonetheless, it is important
  to have reliable price simulations to manage risks, keep the system operating smoothly,
  and encourage investment in infrastructure and technology for the future. Acknowledging
  the past work on anomaly detection in electricity price data, this thesis evaluates existing
  methods on recent German market prices and addresses the challenges faced by them.
  This work proposes a segmented anomaly detection approach for data processing before
  the data is used for calibrating the spot price model. A two-factor electricity spot price
  model with a diffusion factor and a jump factor is implemented. Analysis and inferences
  drawn from studying the impact of the existing and new methods on the data quality are
  presented first. The yield of the respective methods is then evaluated by the calibration
  and simulation performance of the chosen two-factor model. The results support the
  application of segmented approaches presented in this work as they identify jumps with
  higher accuracy, and are able to capture more realised spot price observations in the
  different quantile ranges of the simulated price paths.